Vision System with Tail Detection

1. A vision system comprising: a three-dimensional (3D) camera configured to capture a 3D image of a rearview of a dairy livestock in a stall, wherein: the dairy livestock is oriented in the 3D image with respect to: an x-axis corresponding with a horizontal dimension of the 3D image, a y-axis corresponding with a vertical dimension of the 3D image, and a z-axis corresponding with depth dimension into the 3D image; and each pixel of the 3D image is associated with a depth value along the z-axis; a memory operable to store a thigh gap detection rule set; and a processor operably coupled to the 3D camera and the memory, and configured to: obtain the 3D image; identify one or more regions within the 3D image comprising depth values greater than a depth value threshold; apply the thigh gap detection rule set to the one or more regions to identify a thigh gap region among the one or more regions, wherein the thigh gap region comprises an area between hind legs of the dairy livestock; demarcate an access region within the thigh gap region, wherein the access region is defined by: a first vertical edge, a second vertical edge, a first upper edge spanning between the first vertical edge and the second vertical edge, and a first lower edge spanning between the first vertical edge and the second vertical edge; demarcate a tail detection region, wherein the tail detection region is defined by: a third vertical edge extending vertically from the first vertical edge of the access region, a fourth vertical edge extending vertically from the second vertical edge of the access region, a second upper edge spanning between the third vertical edge and the fourth vertical edge, and a second lower edge spanning between the third vertical edge and the fourth vertical edge, wherein the second lower edge is adjacent to the first upper edge of the access region; partition the 3D image within the tail detection region along the z-axis to generate a plurality of image depth planes; examine each of the plurality of image depth planes, wherein examining each of the plurality of image depth planes comprises: identifying one or more tail candidates within the image depth plane; comparing the one or more tail candidates to a tail model; discarding tail candidates that do not correspond with the tail model; and identifying a tail candidate from among the one or more tail candidates as a tail of the dairy livestock when the tail candidate corresponds with the tail model; and determine position information for the tail of the dairy livestock in response to identifying the tail of the dairy livestock.

2. The system of claim 1 , wherein: the tail model indicates a tail shape; and the tail of the dairy livestock corresponds with the tail shape in at least two of the plurality of depth planes.

3. The system of claim 1 , wherein: the thigh gap detection rule set identifies a marker positioned between the hind legs of the dairy livestock at a lower edge of the 3D image; and applying the thigh gap detection rule set to the one or more regions to identify the thigh gap region comprises: discarding regions from the one or more regions that do not comprise the marker; and identifying a region from among the one or more regions that comprises the marker as the thigh gap region.

4. The system of claim 1 , wherein: the thigh gap detection rule set indicates a minimum area value to be considered the thigh gap region; and applying the thigh gap detection rule set to the one or more regions to identify the thigh gap region comprises: comparing the area of each of the one or more regions to the minimum area value to be considered the thigh gap region; discarding regions from the one or more regions with an area less than the minimum area value to be considered the thigh gap region; and identifying a region from among the one or more regions as the thigh gap region when the region has an area greater than or equal to the minimum area value to be considered the thigh gap region.

5. The system of claim 1 , wherein: the thigh gap detection rule set indicates a maximum height value to be considered the thigh gap region; and applying the thigh gap detection rule set to the one or more regions to identify the thigh gap region comprises: comparing the height of each of the one or more regions to the maximum height value to be considered the thigh gap region; discarding regions from the one or more regions with a height greater than the maximum height value to be considered the thigh gap region; and identifying a region from among the one or more regions as the thigh gap region when the region has a height less than or equal to the maximum height value to be considered the thigh gap region.

6. The system of claim 1 , wherein: the thigh gap detection rule set indicates a minimum width value to be considered the thigh gap region; and applying the thigh gap detection rule set to the one or more regions to identify the thigh gap region comprises: comparing the width of each of the one or more regions to the minimum width value to be considered the thigh gap region; discarding regions from the one or more regions with a width less than the minimum width value to be considered the thigh gap region; and identifying a region from among the one or more regions as the thigh gap region when the region has a width greater than or equal to the minimum width value to be considered the thigh gap region.

7. An apparatus comprising: a memory operable to store a thigh gap detection rule set; and a processor operably coupled to the memory, and configured to: obtain a three-dimensional (3D) image of a rearview of a dairy livestock in a stall, wherein: the dairy livestock is oriented in the 3D image with respect to: an x-axis corresponding with a horizontal dimension of the 3D image, a y-axis corresponding with a vertical dimension of the 3D image, and a z-axis corresponding with depth dimension into the 3D image; and each pixel of the 3D image is associated with a depth value along the z-axis; identify one or more regions within the 3D image comprising depth values greater than a depth value threshold; apply the thigh gap detection rule set to the one or more regions to identify a thigh gap region among the one or more regions, wherein the thigh gap region comprises an area between hind legs of the dairy livestock; demarcate an access region within the thigh gap region, wherein the access region is defined by: a first vertical edge, a second vertical edge, a first upper edge spanning between the first vertical edge and the second vertical edge, and a first lower edge spanning between the first vertical edge and the second vertical edge; demarcate a tail detection region, wherein the tail detection region is defined by: a third vertical edge extending vertically from the first vertical edge of the access region, a fourth vertical edge extending vertically from the second vertical edge of the access region, a second upper edge spanning between the third vertical edge and the fourth vertical edge, and a second lower edge spanning between the third vertical edge and the fourth vertical edge, wherein the second lower edge is adjacent to the first upper edge of the access region; partition the 3D image within the tail detection region along the z-axis to generate a plurality of image depth planes; examine each of the plurality of image depth planes, wherein examining each of the plurality of image depth planes comprises: identifying one or more tail candidates within the image depth plane; comparing the one or more tail candidates to a tail model; discarding tail candidates that do not correspond with the tail model; and identifying a tail candidate from among the one or more tail candidates as a tail of the dairy livestock when the tail candidate corresponds with the tail model; and determine position information for the tail of the dairy livestock in response to identifying the tail of the dairy livestock.

8. The apparatus of claim 7 , wherein: the tail model indicates a tail shape; and the tails of the dairy livestock corresponds with the tail shape in at least two of the plurality of depth planes.

9. The apparatus of claim 7 , wherein: the thigh gap detection rule set identifies a marker positioned between the hind legs of the dairy livestock at a lower edge of the 3D image; and applying the thigh gap detection rule set to the one or more regions to identify the thigh gap region comprises: discarding regions from the one or more regions that do not comprise the marker; and identifying a region from among the one or more regions that comprises the marker as the thigh gap region.

10. The apparatus of claim 7 , wherein: the thigh gap detection rule set indicates a minimum area value to be considered the thigh gap region; and applying the thigh gap detection rule set to the one or more regions to identify the thigh gap region comprises: comparing the area of each of the one or more regions to the minimum area value to be considered the thigh gap region; discarding regions from the one or more regions with an area less than the minimum area value to be considered the thigh gap region; and identifying a region from among the one or more regions as the thigh gap region when the region has an area greater than or equal to the minimum area value to be considered the thigh gap region.

11. The apparatus of claim 7 , wherein: the thigh gap detection rule set indicates a maximum height value to be considered the thigh gap region; and applying the thigh gap detection rule set to the one or more regions to identify the thigh gap region comprises: comparing the height of each of the one or more regions to the maximum height value to be considered the thigh gap region; discarding regions from the one or more regions with a height greater than the maximum height value to be considered the thigh gap region; and identifying a region from among the one or more regions as the thigh gap region when the region has a height less than or equal to the maximum height value to be considered the thigh gap region.

12. The apparatus of claim 7 , wherein: the thigh gap detection rule set indicates a minimum width value to be considered the thigh gap region; and applying the thigh gap detection rule set to the one or more regions to identify the thigh gap region comprises: comparing the width of each of the one or more regions to the minimum width value to be considered the thigh gap region; discarding regions from the one or more regions with a width less than the minimum width value to be considered the thigh gap region; and identifying a region from among the one or more regions as the thigh gap region when the region has a width greater than or equal to the minimum width value to be considered the thigh gap region.

13. A tail detection method comprising: obtaining, by a processor, a three-dimensional (3D) image of a rearview of a dairy livestock in a stall, wherein: the dairy livestock is oriented in the 3D image with respect to: an x-axis corresponding with a horizontal dimension of the 3D image, a y-axis corresponding with a vertical dimension of the 3D image, and a z-axis corresponding with depth dimension into the 3D image; and each pixel of the 3D image is associated with a depth value along the z-axis; identifying, by the processor, one or more regions within the 3D image comprising depth values greater than a depth value threshold; applying, by the processor, a thigh gap detection rule set to the one or more regions to identify a thigh gap region among the one or more regions, wherein the thigh gap region comprises an area between hind legs of the dairy livestock; demarcating, by the processor, an access region within the thigh gap region, wherein the access region is defined by: a first vertical edge, a second vertical edge, a first upper edge spanning between the first vertical edge and the second vertical edge, and a first lower edge spanning between the first vertical edge and the second vertical edge; demarcating, by the processor, a tail detection region, wherein the tail detection region is defined by: a third vertical edge extending vertically from the first vertical edge of the access region, a fourth vertical edge extending vertically from the second vertical edge of the access region, a second upper edge spanning between the third vertical edge and the fourth vertical edge, and a second lower edge spanning between the third vertical edge and the fourth vertical edge, wherein the second lower edge is adjacent to the first upper edge of the access region; partitioning, by the processor, the 3D image within the tail detection region along the z-axis to generate a plurality of image depth planes; examining, by the processor, each of the plurality of image depth planes, wherein examining each of the plurality of image depth planes comprises: identifying one or more tail candidates within the image depth plane; comparing the one or more tail candidates to a tail model; discarding tail candidates that do not correspond with the tail model; and identifying a tail candidate from among the one or more tail candidates as a tail of the dairy livestock when the tail candidate corresponds with the tail model; and determining, by the processor, position information for the tail of the dairy livestock in response to identifying the tail of the dairy livestock.

14. The method of claim 13 , wherein: the tail model indicates a tail shape; and the tail of the dairy livestock corresponds with the tail shape in at least two of the plurality of depth planes.

15. The method of claim 13 , wherein: demarcating the access region comprises reducing the width of the access region with respect to the x-axis, and reducing the width of the access region comprises: shifting the first vertical edge toward the second vertical edge; and shifting the second vertical edge toward the first vertical edge.

16. The method of claim 13 , wherein the tail model is an ellipse.

17. The method of claim 13 , wherein: the thigh gap detection rule set identifies a marker positioned between the hind legs of the dairy livestock at a lower edge of the 3D image; and applying the thigh gap detection rule set to the one or more regions to identify the thigh gap region comprises: discarding regions from the one or more regions that do not comprise the marker; and identifying a region from among the one or more regions that comprises the marker as the thigh gap region.

18. The method of claim 13 , wherein: the thigh gap detection rule set indicates a minimum area value to be considered the thigh gap region; and applying the thigh gap detection rule set to the one or more regions to identify the thigh gap region comprises: comparing the area of each of the one or more regions to the minimum area value to be considered the thigh gap region; discarding regions from the one or more regions with an area less than the minimum area value to be considered the thigh gap region; and identifying a region from among the one or more regions as the thigh gap region when the region has an area greater than or equal to the minimum area value to be considered the thigh gap region.

19. The method of claim 13 , wherein: the thigh gap detection rule set indicates a maximum height value to be considered the thigh gap region; and applying the thigh gap detection rule set to the one or more regions to identify the thigh gap region comprises: comparing the height of each of the one or more regions to the maximum height value to be considered the thigh gap region; discarding regions from the one or more regions with a height greater than the maximum height value to be considered the thigh gap region; and identifying a region from among the one or more regions as the thigh gap region when the region has a height less than or equal to the maximum height value to be considered the thigh gap region.

20. The method of claim 13 , wherein: the thigh gap detection rule set indicates a minimum width value to be considered the thigh gap region; and applying the thigh gap detection rule set to the one or more regions to identify the thigh gap region comprises: comparing the width of each of the one or more regions to the minimum width value to be considered the thigh gap region; discarding regions from the one or more regions with a width less than the minimum width value to be considered the thigh gap region; and identifying a region from among the one or more regions as the thigh gap region when the region has a width greater than or equal to the minimum width value to be considered the thigh gap region.